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AbstractThis paper examines the incorporation of useful information extracted from the evolutionary process, in order to improve algorithm performance. In order to achieve this objective, we introduce an efficient method… Click to show full abstract
AbstractThis paper examines the incorporation of useful information extracted from the evolutionary process, in order to improve algorithm performance. In order to achieve this objective, we introduce an efficient method of extracting and utilizing valuable information from the evolutionary process. Finally, this information is utilized for optimizing the search process. The proposed algorithm is compared with the NSGAII for solving some real-world instances of the fuzzy portfolio optimization problem. The proposed algorithm outperforms the NSGAII for all examined test instances.
Journal Title: Annals of Operations Research
Year Published: 2019
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